ارزیابی کارایی روش نیمه کمّی مدل AquaCrop برای پیش‌بینی رشد تربچه با سطوح مختلف کود نیتروژن

نوع مقاله : مقاله پژوهشی

نویسندگان

1 داتشجوی ارشد گروه مهندسی آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران، پاکدشت، ایران

2 استاد گروه مهندسی آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران، پاکدشت، ایران

3 استادیار گروه علوم باغبانی، پردیس ابوریحان، دانشگاه تهران، پاکدشت، ایران

چکیده

در این پژوهش کارایی روش نیمه کمی(Semi-quantitative)  در مدل شبیه‌سازی رشد گیاه(AquaCrop)  برای پیش‌بینی زیست‌توده و پوشش گیاهی تحت مدیریت‌های مختلف کود نیتروژن از طریق مقایسه پارامترهای شبیه‌سازی‌شده با نتایج اندازه‌گیری در گلخانه ارزیابی گردید. گیاه تربچه رقم چریبل (cherrybel) طی دو دوره (بهمن ماه 1396 و فروردین 1397) در گلخانه پردیس ابوریحان دانشگاه تهران، بدون تنش آبی و حرارتی کشت شد. آزمایش به صورت طرح بلوک‌های کامل تصادفی تحت تیمارهای مختلف کودی صفر به عنوان شاهد (N0)، 50(N1) ، 100(N2)، 150 (N3)، 200 (N4)، 250 کیلوگرم نیتروژن در هکتار(N5) ، به صورت اوره با سه تکرار انجام شد. داده­های تیمار N0 و N3 در کشت اول برای واسنجی­ و سایر داده­ها برای صحت­سنجی مدل استفاده گردید. برای ارزیابی عملکرد مدل از شاخص‌های آماری ریشه میانگین مربعات خطای نسبی (RRMSE)، ضریب تعیین (R2) و متوسط خطای اریب (MBE) استفاده شد. در مرحله واسنجی مقدار این پارامترها در شبیه­سازی زیست‌توده به ترتیب برابر%12/11، 973/0، 032/0 تن در هکتار برای N0 و %32/10، 975/0 و 002/0- تن در هکتار برای N3 و در شبیه­سازی پوشش گیاهی به ترتیب%93/15، 884/0 و %30/4 برای N0 و % 84/12، 916/0 و %94/5 برای N3 به دست آمد. همچنین در مرحله صحت­سنجی محدوده تغییرات این مقادیر در پیش‌بینی زیست‌توده به ترتیب برابر % 7/25-7/13، 988/0-923/0 و 118/0-110/0- تن در هکتار و در پیش‌بینی پوشش گیاهی به ترتیب % 4/25-19، 867/0-768/0 و % 8/10-7/5 به دست آمد. بر اساس نتایج، مدل AquaCrop، زیست‌توده و پوشش گیاهی را تحت سطوح مختلف کود نیتروژن با دقت بالایی در طول دوره رشد گیاه شبیه‌سازی نمود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Performance Evaluation of the AquaCrop Semi-quantitative Method for Prediction of Radish Growth under Different Levels of Nitrogen Fertilizer

نویسندگان [English]

  • Parisa Ataei 1
  • Ali Rahimikhoob 2
  • Mostafa Arab 3
1 Master Science Student, Department of Irrigation and Drainage Engineering, Aburaihan Campus, University of Tehran,Pakdasht,Iran.
2 Professor, Department of Irrigation and Drainage Engineering, Aburaihan Campus, University of Tehran, Pakdasht, Iran.
3 Assistance Professor, Department of Horticulture, Aburaihan Campus, University of Tehran, Pakdasht, Iran.
چکیده [English]

In this research, the performance of semi-quantitative method in AquaCrop model for prediction of biomass and vegetation under various nitrogen fertilizer managements was evaluated by comparing the simulated parameters with the measured results in the greenhouse. The radish cherrybel cultivar was cultivated in the greenhouse of Pardis Aburaihan, University of Tehran without thermal and water stress during two periods (February 2018 and April 2018). The experiment was conducted as a randomized complete block design with different treatments such as zero fertilizer as control (N0), 50 (N1), 100 (N2), 150 (N3), 200 (N4), 250 kg nitrogen per hectare (N5), using Urea fertilizer with three replications. N0 and N3 treatment data of the first cultivation period were used for calibration and the other data were applied for model validation. Relative Root Mean Square Error (RRMSE), Determination Coefficient (R2) and Mean Bios Error (MBE) were used to evaluate the performance of model. The values of these parameters (RRMSE, R2 and MBE) for biomass simulation were 11.12%, 0.973, 0.032 ton.ha-1, respectively for N0 and 10.32%, 0.975, and -0.002 ton.ha-1, respectively for N3 in the calibration step. These parameters for canopy cover simulation were 15.93%, 0.884 and 4.30%, respectively for N0 and 12.84%, 0.916 and 5.94%, respectively for N3 in the calibration step. Also, in the validation step, the range of changes in these parameters for biomass simulation were 13.7-25.7%, 0.923-0.988, -0.110-0.118 ton.ha-1 and for canopy cover simulation were 19-25.4%, 0.768-0.867, 5.7-10.18%, respectively. Based on the results, AquaCrop model simulated the biomass and canopy cover precisely under different levels of nitrogen fertilizer and during the growing period.

کلیدواژه‌ها [English]

  • AquaCrop
  • nitrogen
  • radish
  • semi-quantitative method
Akumaga, U., Tarhule, A. and Yusuf, A. A. (2017). Validation and testing of the FAO AquaCrop model under different levels of nitrogen fertilizer on rainfed maize in Nigeria, West Africa. Agricultural and Forest Meteorology, 232, 225–234.
Ata-Ul-Karim, S. T., Yao, X., Liu, X., Cao, W. and Zhu, Y. (2014). Determination of Critical Nitrogen Dilution Curve Based on Stem Dry Matter in Rice. PLoS ONE, 9(8), https://doi.org/10.1371/journal.pone.0104540.
Berenguer, P., Santiveri, F., Bioxadera, J. and Lioveras, J. (2009). Nitrojen fertilization of irrigated maize under Mediterranean conditions. European Journal of Agronomy. 30(3), 163-171.
Guler, S. (2006). Developments on fertilizer consumption of the world and Turkey. Journal of the Faculty of Agriculture, 21(2), 243-248.
Harmanto, V.M.S., M.S. Babel and H.J. Tantau. 2005. Water requirement of drip irrigated tomatoes grown in greenhouse in tropical environment. Agric. Water Manage.71:225-242
Hasani, A. and Nourzadeh-Haddad, M. (2016). Effect of Ammonium Nitrate and Free Amino Acids on the Nitrate
Accumulation in Radish. Water and Soil Science- University of Tabriz, 26(4.1), 67-78. (In Farsi)
Hopkins, W. G. (2004). Introduction to Plant Physiology (3th ed.). New York: Wiely. pp. 557.
Hsiao, T. C., Heng, L., Steduto, P., Rojas-lara, B., Raes, D. and Fereres, E. (2009). AquaCrop the FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal, 101(3), 448–459.
Jamieson, P. D., Porter, J. R. and Wilson, D. R. (1991). A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crops Research, 27(4), 337-350.
Khorsand, A., Verdinejad, V. R. and Shahidi, A. (2014). Comparison of FAO Aquacrop and SWAP agro-hydrological models to simulate water and salt transport during growing season of winter wheat. International Journal of Biosciences. 11(4), 223-233.
Kroes, J. G. and Van Dam, J. C. (2008). Reference manual SWAP version 3.2. Alterra green world Research. Wagennigen. Report 1649. Avaiabel at: http://www.swap. Alterra.nl.
Malakouti, M. J. (2011). Relationship between Balanced Fertilization and Healthy Agricultural Products (A Review). Journal of Crop and Weed Ecophysiology, 4(16), 133-152. (In Farsi)
Patrignani, A. and Ochsner, T.E.(2015). Canopeo: A Powerful New Tool for Measuring Fractional Green Canopy Cover. Agronomy Journal, 107(6), 2312-2320.
Powlson, D. S., Addiscott, T. M. and Benjamin, N. (2008). When does nitrate become a risk for humans. Journal of Environmental Quality. 37(2), 291–295.
Raes, D., Steduto, P., Hsiao, T. C. and Fereres, E. (2009). AquaCrop - the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agronomy Journal, 101(3), 438–447.
Raes, D., Steduto, P., Hsiao, T. C. and Fereres, E. (2012). AquaCrop Reference Manual, AquaCrop version 4.0. Rome, Italy: FAO.
Rahimikhoob, H., Sotoodehnia, A. and Massahbavani, A. R. (2014). Calibration and Evaluation of AquaCrop for Maize in Qazvin Region. Iranian Journal of Irrigation and Drainage, 8(1), 108-115. (In Farsi)
Ramos, T. B., Šimunek, J., Goncalves, M. C., Martins, J. C., Prazeres, A. and Pereira, L.S. (2012). Two dimensional modeling of water and nitrogen fate from sweet sorghum irrigated with fresh and blended saline waters. Agricultural Water Management. 111, 87–104.
Ranjbar, A., Rahimikhoob, A. and Ebrahimian, H. (2017). Evaluating Semi-Quantitative Approach of the AquaCrop Model for Simulating Maize Response to Nitrogen Fertilizer. Iranian Journal of Irrigation and Drainage, 11(2), 286-298. (In Farsi)
Russo, D. and Bakker, D. (1986). Crop water production function for sweet corn and cotton irrigated and saline water. Soil science societyand American journal. 51(6), 1554-1562.
Sepaskhah, A. R, Bazafshan, A. R. and Shirmohammadi-Aliakbbarian, Z. (2006). Development and evaluation of model for yield production of wheat, maize and sugarbeet under water and salt stresses. Biosystems enginerring. 93(2), 139-152.
Steduto, P., Hsiao, T. C., Raes, D. and Fereres, E. (2009). AquaCrop: The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agronomy Journal, 101(3), 426-437.
Steduto, P., Hsiao, T. C. and Fereres, E. (2007). On the conservative behavior of biomass water productivity. Irrigation Science. 25(3), 189–207.
Stefanelli, D. S., Brady, S., Winkler, R. B., Jones, J. and Tomkins, B. T. (2012). Lettuce (Lactuca sativa L.) growth and quality response to applied nitrogen under hydroponic conditions. Acta Agriculturae, 927, 353–360.
Stockle, C. O., Donatelli, M. and Nelson, R. (2003). CropSyst, a cropping systems simulation model. European Journal of Agronomy, 18(3), 289-307.
Stricevic, R., Dzeletovic, Z., Djurovic, N. and Cosic, M. (2014). Application of the AquaCrop model to simulate the biomass of Miscanthus x giganteus under different nutrient supply conditions. GCB Bioenergy, 7(6), 1203-1210.
Van Gaelen, H., Tsegay, A., Delbecque, N., Shrestha, N., Garcia, M., Fajardo, H., Miranda, R., Vanuytrecht, E., Abrha, B., Diels, J. and Raes, D. (2014). A semi-quantitative approach for modelling crop response to soil fertility: evaluation of the Aquacrop procedure. Journal of Agricultural Science, 153(7), 1218-1233.